1Psychology of Personality Research MethodsKatherine Aumer-Ryan Lecture 2 2Personality Psychology as a unique science--Every assumption should be and often is questioned--Methodology and Statistical use of primary importance--The primary purpose of science is to understand what is known and to discover/explore what is yet to be known. NOT a technical or trade school lesson. 3The Data--3 important qualities of data--Reliability--Validity--Generalizability--Can you guess what they mean?How can someones argument be valid?What does it mean to like people, in general?How is a car reliable? 4To be concerned about these qualities of data, we need to have collected data in order to answer a research question.--First, we have to want to measure something. For example How friendly are the people in this class? Who is the most conscientious? How emotionally stable are the people in the front row? --What we want to measure is a trait. How is this different from a state?--What circumstances are relevant when we want to measure a state versus a trait? 5--State v. Trait--Lets say we are trying to measure general happiness amongst UH students.--Research question How happy are students at UH?--What kind of data do we use use the S in the BLIS--When should we ask students?--Right after a football game where UH won?--Only in the mornings?--After the Ka Leo has announced increases in UH tuition?--At the end of semester, before or after finals? 6--State v. Trait--States are temporary and passing (e.g., bad mood, hyper) --Traits are stable and do not change much over time (e.g., conscientious, open, or extraverted) --importantly traits, unlike states, are what make us unique. We each differ on various traits, which allows us to be different from one another. --Once we have the research question, trait defined, and know what kind of data we want to collect we have to ensure the data are reliable, valid, and generalizable. 7What is reliable data?--Scientifically reliable data is free of (or minimally impacted by) measurement error. --What is measurement error? 8Things that can make our measurement of students happiness unreliableWhat we as researchers can do to prevent this--Being especially careful. Double/triple check--Low precision--State of the participant--Not too much you can do. Try to sample from random times.--State of the experimenter--Make sure each experimenter gets the same training--Environment--Standardize the environment as much as you can. Same room, same temperature 9Aggregation--Probably the best thing one can do to get a reliable result.--Requires sampling same person, over and over again.--Relies on the principle that Random effects sum to zero.--Can require taking the same test over and over again, or having similar questions on the same test be asked over and over again. 10--Validity--the degree to which a measure actually reflects what one thinks or hope it does.--Construct Validity the degree to which a measure (e.g., a psychological test) actually reflects the components of a psychological construct (e.g., intelligence, sociability, conservatism, passionate love, racism)--How would our measure of UH Students Happiness show construct validity? 11Generalizability--How do these data apply, pertain, be indicative of, other populations, people, time, place--Encompasses BOTH reliability and validity.--Current issues of generalizability with psychology studiesCollege studentsGenderParticipationCohortRace and Culture 12Results of Your Graphology tests--First look at only your results. Think about how well they pertain to you.--Fill out the survey again.--Answer an additional question How accurate is my personality profile? 1 2 3 4 5 6 7 8 9 Not at all Completely 13GraphologyQuestions or Comments?--What do you think of Graphology?--What do you think of your results?Forer (Barnum) Effect--Personal Validation Effect a very general, vague statement about ones personality that actually applies to everyone.--Practiced by astrology, palm reading, fortune telling, tarot card reading--Used by pseudoscience. 14How Scientific are these disciplines?--Your pretest results--Do you think your posttest scores will differ? 15Break time 16--Research Design--In order to gather data, one needs to have an approach, specifically a design.--3 Main types of Research Design--Case Study single, isolated example.--Experimental manipulation of variable.--Correlational assesses relationships, no manipulation. 17--Case Studies or Method--Involves very close study of a single incident, person, or phenomenon. --For exampleYou (introspection)Any personNatural DisasterRare cases, like with PDsRare people 18ProsConsCase Studies-Lots of information-No controlvariables going everywhere!-Generate theory, ideas, prepare for future-Can you really generalize?-Cant get the information any other way 19Experimental--Random assignment of participants, variable is manipulated, and outcome is measured. 20ProsConsCase Studies-Lots of information-No controlvariables going everywhere!-Generate theory, ideas, prepare for future-Can you really generalize?-Cant get the information any other way-May create artificial groups.Experimental-Infer causality-Can make theoretical and pragmatic claims-Unethical (e.g., deception) or impossible. 21Correlational--Peoples emotions, behaviors, and/or cognitions are surveyed and a relationship is inferred. No manipulation of variables. 22ProsConsCase Studies-Lots of information-No controlvariables going everywhere!-Generate theory, ideas, prepare for future-Can you really generalize?-Cant get the information any other way-May create artificial groups.Experimental-Infer causality-Can make theoretical and pragmatic claims-Unethical (e.g., deception) or impossible.-Relatively easy to implementCorrelational-Cannot infer causality-Third variable problem-Can be more realistic--sometimes 23--How do we know we have a significant result?--Significance testing what is the probability that my data was due to chance? (plt.05)--Correlations how strong is the relationship between two variables? ( or - ) 24--In any research design there is the probability for error--Type I Deciding there is an effect when none exists. --Type II Deciding there is NOT an effect when one DOES exist. --Ethics--Generalizability is your study applicable to many people? If only to a few, shouldnt you just study those few or have a representative sample.--Truthfulness dont make up data.--Deception is it needed? Knowingly telling a lie? 25--Break and video 26--Class Overview--What are your predictions for how scientific is the field--Get on facebook and join the class group--Chapter 3 First part--What are the three qualities of data?--Difference between State and Trait?--Aggregation can increase--Chapter 3 Second part --3 main types of research design?--Type I and II errors?--Ethical problems? (name 3)

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